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ICML
2003
IEEE
16 years 4 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
107
Voted
FLAIRS
1998
15 years 4 months ago
Learning to Race: Experiments with a Simulated Race Car
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
Larry D. Pyeatt, Adele E. Howe
COLT
2004
Springer
15 years 8 months ago
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
Constantine Caramanis, Shie Mannor
CC
2001
Springer
15 years 7 months ago
Points-to and Side-Effect Analyses for Programs Built with Precompiled Libraries
Large programs are typically built from separate modules. Traditional whole-program analysis cannot be used in the context of such modular development. In this paper we consider an...
Atanas Rountev, Barbara G. Ryder
ISCAS
2008
IEEE
169views Hardware» more  ISCAS 2008»
15 years 9 months ago
Sigma-delta learning for super-resolution independent component analysis
— Many source separation algorithms fail to deliver robust performance in presence of artifacts introduced by cross-channel redundancy, non-homogeneous mixing and highdimensional...
Amin Fazel, Shantanu Chakrabartty